Browsing by Author "Donner, Reik V."
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- ItemBilateral Trade Agreements and the Interconnectedness of Global Trade(Lausanne : Frontiers Media, 2018) Maluck, Julian; Glanemann, Nicole; Donner, Reik V.Over the last decades, bilateral trade agreements (BTAs) have increased considerably in number and economic relevance. Notably, such agreements substantially affect global trade, since the reorganization of flows of goods and services has prominent impacts on the contracting countries' economies, but also on other parties that are (directly or indirectly) engaged in trade with these countries. Here, we empirically study the effect of BTAs on the input-output linkages between the contractual parties' national economic sectors by defining a new measure of Trade Interconnectedness (TI), which describes the relative importance of direct and indirect production linkages between the two countries in the international trade network. By analyzing its time evolution for each pair of trade agreement partners, we demonstrate that while most BTAs are succeeded by an increase in TI between the contractors, there are some notable exceptions. In particular, comparing the trade profiles of China and the United States (US), we find indications that both countries have been pursuing fundamentally different objectives and strategies related to the negotiation of BTAs.
- ItemCausal coupling inference from multivariate time series based on ordinal partition transition networks(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2021) Subramaniyam, Narayan Puthanmadam; Donner, Reik V.; Caron, Davide; Panuccio, Gabriella; Hyttinen, JariIdentifying causal relationships is a challenging yet crucial problem in many fields of science like epidemiology, climatology, ecology, genomics, economics and neuroscience, to mention only a few. Recent studies have demonstrated that ordinal partition transition networks (OPTNs) allow inferring the coupling direction between two dynamical systems. In this work, we generalize this concept to the study of the interactions among multiple dynamical systems and we propose a new method to detect causality in multivariate observational data. By applying this method to numerical simulations of coupled linear stochastic processes as well as two examples of interacting nonlinear dynamical systems (coupled Lorenz systems and a network of neural mass models), we demonstrate that our approach can reliably identify the direction of interactions and the associated coupling delays. Finally, we study real-world observational microelectrode array electrophysiology data from rodent brain slices to identify the causal coupling structures underlying epileptiform activity. Our results, both from simulations and real-world data, suggest that OPTNs can provide a complementary and robust approach to infer causal effect networks from multivariate observational data.
- ItemA climate network perspective on the intertropical convergence zone(Göttingen : Copernicus Publ., 2021) Wolf, Frederik; Voigt, Aiko; Donner, Reik V.The intertropical convergence zone (ITCZ) is an important component of the tropical rain belt. Climate models continue to struggle to adequately represent the ITCZ and differ substantially in its simulated response to climate change. Here we employ complex network approaches, which extract spatiotemporal variability patterns from climate data, to better understand differences in the dynamics of the ITCZ in state-of-the-art global circulation models (GCMs). For this purpose, we study simulations with 14 GCMs in an idealized slab-ocean aquaplanet setup from TRACMIP – the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project. We construct network representations based on the spatial correlation patterns of monthly surface temperature anomalies and study the zonal-mean patterns of different topological and spatial network characteristics. Specifically, we cluster the GCMs by means of the distributions of their zonal network measures utilizing hierarchical clustering. We find that in the control simulation, the distributions of the zonal network measures are able to pick up model differences in the tropical sea surface temperature (SST) contrast, the ITCZ position, and the strength of the Southern Hemisphere Hadley cell. Although we do not find evidence for consistent modifications in the network structure tracing the response of the ITCZ to global warming in the considered model ensemble, our analysis demonstrates that coherent variations of the global SST field are linked to ITCZ dynamics. This suggests that climate networks can provide a new perspective on ITCZ dynamics and model differences therein.
- ItemCommon solar wind drivers behind magnetic storm–magnetospheric substorm dependency([London] : Macmillan Publishers Limited, part of Springer Nature, 2018) Runge, Jakob; Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Donner, Reik V.The dynamical relationship between magnetic storms and magnetospheric substorms is one of the most controversial issues of contemporary space research. Here, we address this issue through a causal inference approach to two corresponding indices in conjunction with several relevant solar wind variables. We find that the vertical component of the interplanetary magnetic field is the strongest and common driver of both storms and substorms. Further, our results suggest, at least based on the analyzed indices, that there is no statistical evidence for a direct or indirect dependency between substorms and storms and their statistical association can be explained by the common solar drivers. Given the powerful statistical tests we performed (by simultaneously taking into account time series of indices and solar wind variables), a physical mechanism through which substorms directly or indirectly drive storms or vice versa is, therefore, unlikely.
- ItemCoupled network analysis revealing global monthly scale co-variability patterns between sea-surface temperatures and precipitation in dependence on the ENSO state(Berlin ; Heidelberg : Springer, 2021) Ekhtiari, Nikoo; Ciemer, Catrin; Kirsch, Catrin; Donner, Reik V.The Earth’s climate is a complex system characterized by multi-scale nonlinear interrelationships between different subsystems like atmosphere and ocean. Among others, the mutual interdependence between sea surface temperatures (SST) and precipitation (PCP) has important implications for ecosystems and societies in vast parts of the globe but is still far from being completely understood. In this context, the globally most relevant coupled ocean–atmosphere phenomenon is the El Niño–Southern Oscillation (ENSO), which strongly affects large-scale SST variability as well as PCP patterns all around the globe. Although significant achievements have been made to foster our understanding of ENSO’s global teleconnections and climate impacts, there are many processes associated with ocean–atmosphere interactions in the tropics and extratropics, as well as remote effects of SST changes on PCP patterns that have not yet been unveiled or fully understood. In this work, we employ coupled climate network analysis for characterizing dominating global co-variability patterns between SST and PCP at monthly timescales. Our analysis uncovers characteristic seasonal patterns associated with both local and remote statistical linkages and demonstrates their dependence on the type of the current ENSO phase (El Niño, La Niña or neutral phase). Thereby, our results allow identifying local interactions as well as teleconnections between SST variations and global precipitation patterns.
- ItemDetecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis(Katlenburg-Lindau : European Geophysical Society, 2020) Lekscha, Jaqueline; Donner, Reik V.Analysing palaeoclimate proxy time series using windowed recurrence network analysis (wRNA) has been shown to provide valuable information on past climate variability. In turn, it has also been found that the robustness of the obtained results differs among proxies from different palaeoclimate archives. To systematically test the suitability of wRNA for studying different types of palaeoclimate proxy time series, we use the framework of forward proxy modelling. For this, we create artificial input time series with different properties and compare the areawise significant anomalies detected using wRNA of the input and the model output time series. Also, taking into account results for general filtering of different time series, we find that the variability of the network transitivity is altered for stochastic input time series while being rather robust for deterministic input. In terms of significant anomalies of the network transitivity, we observe that these anomalies may be missed by proxies from tree and lake archives after the non-linear filtering by the corresponding proxy system models. For proxies from speleothems, we additionally observe falsely identified significant anomalies that are not present in the input time series. Finally, for proxies from ice cores, the wRNA results show the best correspondence to those for the input data. Our results contribute to improve the interpretation of windowed recurrence network analysis results obtained from real-world palaeoclimate time series.
- ItemDisentangling nonlinear geomagnetic variability during magnetic storms and quiescence by timescale dependent recurrence properties(Les Ulis : EDP Sciences, 2020) Alberti, Tommaso; Lekscha, Jaqueline; Consolini, Giuseppe; De Michelis, Paola; Donner, Reik V.Understanding the complex behavior of the near-Earth electromagnetic environment is one of the main challenges of Space Weather studies. This includes both the correct characterization of the different physical mechanisms responsible for its configuration and dynamics as well as the efforts which are needed for a correct forecasting of several phenomena. By using a nonlinear multi-scale dynamical systems approach, we provide here new insights into the scale-to-scale dynamical behavior of both quiet and disturbed periods of geomagnetic activity. The results show that a scale-dependent dynamical transition occurs when moving from short to long timescales, i.e., from fast to slow dynamical processes, the latter being characterized by a more regular behavior, while more dynamical anomalies are found in the behavior of the fast component. This suggests that different physical processes are typical for both dynamical regimes: the fast component, being characterized by a more chaotic and less predictable behavior, can be related to the internal dynamical state of the near-Earth electromagnetic environment, while the slow component seems to be less chaotic and associated with the directly driven processes related to the interplanetary medium variability. Moreover, a clear difference has been found between quiet and disturbed periods, the former being more complex than the latter. These findings support the view that, for a correct forecasting in the framework of Space Weather studies, more attention needs to be devoted to the identification of proxies describing the internal dynamical state of the near-Earth electromagnetic environment. © T. Alberti et al., Published by EDP Sciences 2020.
- ItemAn early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures(Bristol : IOP Publ., 2020) Ciemer, Catrin; Rehm, Lars; Kurths, Jürgen; Donner, Reik V.; Winkelmann, Ricarda; Boers, NiklasDroughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.
- ItemEffects of the Lake Sobradinho Reservoir (Northeastern Brazil) on the Regional Climate(Basel : MDPI, 2017) Ekhtiari, Nikoo; Grossman-Clarke, Susanne; Koch, Hagen; de Souza, Werônica Meira; Donner, Reik V.; Volkholz, JanThis study investigates the effects of Lake Sobradinho, a large reservoir in Northeastern Brazil, on the local near-surface atmospheric and boundary layer conditions. For this purpose, simulations with the regional climate model COSMO-CLM are compared for two different scenarios: (1) with the lake being replaced by the average normal native vegetation cover and (2) with the lake as it exists today, for two different two-month periods reflecting average and very dry conditions, respectively. The performance of the simulation is evaluated against data from surface meteorological stations as well as satellite data in order to ensure the model’s ability to capture atmospheric conditions in the vicinity of Lake Sobradinho. The obtained results demonstrate that the lake affects the near-surface air temperature of the surrounding area as well as its humidity and wind patterns. Specifically, Lake Sobradinho cools down the air during the day and warms it up during the night by up to several ∘ C depending on the large-scale meteorological conditions. Moreover, the humidity is significantly increased as a result of the lake’s presence and causes a lake breeze. The observed effects on humidity and air temperature also extend over areas relatively far away from the lake.
- ItemEvolving climate network perspectives on global surface air temperature effects of ENSO and strong volcanic eruptions(Berlin ; Heidelberg : Springer, 2021) Kittel, Tim; Ciemer, Catrin; Lotfi, Nastaran; Peron, Thomas; Rodrigues, Francisco; Kurths, Jürgen; Donner, Reik V.Episodically occurring internal (climatic) and external (non-climatic) disruptions of normal climate variability are known to both affect spatio-temporal patterns of global surface air temperatures (SAT) at time-scales between multiple weeks and several years. The magnitude and spatial manifestation of the corresponding effects depend strongly on the specific type of perturbation and may range from weak spatially coherent yet regionally confined trends to a global reorganization of co-variability due to the excitation or inhibition of certain large-scale teleconnectivity patterns. Here, we employ functional climate network analysis to distinguish qualitatively the global climate responses to different phases of the El Niño–Southern Oscillation (ENSO) from those to the three largest volcanic eruptions since the mid-20th century as the two most prominent types of recurrent climate disruptions. Our results confirm that strong ENSO episodes can cause a temporary breakdown of the normal hierarchical organization of the global SAT field, which is characterized by the simultaneous emergence of consistent regional temperature trends and strong teleconnections. By contrast, the most recent strong volcanic eruptions exhibited primarily regional effects rather than triggering additional long-range teleconnections that would not have been present otherwise. By relying on several complementary network characteristics, our results contribute to a better understanding of climate network properties by differentiating between climate variability reorganization mechanisms associated with internal variability versus such triggered by non-climatic abrupt and localized perturbations.
- ItemImpact of temperature and precipitation extremes on the flowering dates of four German wildlife shrub species(München : European Geopyhsical Union, 2016) Siegmund, Jonatan F.; Wiedermann, Marc; Donges, Jonathan F.; Donner, Reik V.Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions have already been shown to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. Studying this question calls for the application of statistical methods that are tailored to the specific properties of event time series. Here, we employ event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences in order to systematically quantify simultaneities between meteorological extremes and the timing of the flowering of four shrub species across Germany. Our study confirms previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of the investigated plants. However, previous studies solely based on correlation analysis do not allow deriving explicit estimates of the strength of such interdependencies without further assumptions, a gap that is closed by our analysis. In addition to direct impacts of extremely warm and cold spring temperatures, our analysis reveals statistically significant indications of an influence of temperature extremes in the autumn preceding the flowering.
- ItemImpacts of temperature extremes on European vegetation during the growing season(München : European Geopyhsical Union, 2017) Baumbach, Lukas; Siegmund, Jonatan F.; Mittermeier, Magdalena; Donner, Reik V.Temperature is a key factor controlling plant growth and vitality in the temperate climates of the mid-latitudes like in vast parts of the European continent. Beyond the effect of average conditions, the timings and magnitudes of temperature extremes play a particularly crucial role, which needs to be better understood in the context of projected future rises in the frequency and/or intensity of such events. In this work, we employ event coincidence analysis (ECA) to quantify the likelihood of simultaneous occurrences of extremes in daytime land surface temperature anomalies (LSTAD) and the normalized difference vegetation index (NDVI). We perform this analysis for entire Europe based upon remote sensing data, differentiating between three periods corresponding to different stages of plant development during the growing season. In addition, we analyze the typical elevation and land cover type of the regions showing significantly large event coincidences rates to identify the most severely affected vegetation types. Our results reveal distinct spatio-temporal impact patterns in terms of extraordinarily large co-occurrence rates between several combinations of temperature and NDVI extremes. Croplands are among the most frequently affected land cover types, while elevation is found to have only a minor effect on the spatial distribution of corresponding extreme weather impacts. These findings provide important insights into the vulnerability of European terrestrial ecosystems to extreme temperature events and demonstrate how event-based statistics like ECA can provide a valuable perspective on environmental nexuses.
- ItemMeridionally Extending Anomalous Wave Train over Asia During Breaks in the Indian Summer Monsoon([Cham] : Springer International Publishing, 2019) Umakanth, Uppara; Vellore, Ramesh K.; Krishnan, R.; Choudhury, Ayantika Dey; Bisht, Jagat S.H.; Di Capua, Giorgia; Coumou, Dim; Donner, Reik V.Anomalous interactions between the Indian summer monsoon (ISM) circulation and subtropical westerlies are known to trigger breaks in the ISM on subseasonal time-scales, characterised by a pattern of suppressed rainfall over central-north India, and enhanced rainfall over the foothills of the central–eastern Himalayas (CEH). An intriguing feature during ISM breaks is the formation of a mid-tropospheric cyclonic circulation anomaly extending over the subtropical and mid-latitude areas of the Asian continent. This study investigates the mechanism of the aforesaid Asian continental mid-tropospheric cyclonic circulation (ACMCC) anomaly using observations and simplified model experiments. The results of our study indicate that the ACMCC during ISM breaks is part of a larger meridional wave train comprising of alternating anticyclonic and cyclonic anomalies that extend poleward from the monsoon region to the Arctic. A lead–lag analysis of mid-tropospheric circulation anomalies suggests that the meridional wave-train generation is linked to latent heating (LH) anomalies over the CEH foothills, Indo-China, and the Indian landmass during ISM breaks. By conducting sensitivity experiments using a simplified global atmospheric general circulation model forced with satellite-derived three-dimensional LH, it is demonstrated that the combined effects of the enhanced LH over the CEH foothills and Indo-China and decreased LH over the Indian landmass during ISM breaks are pivotal for generating the poleward extending meridional wave train and the ACMCC anomaly. At the same time, the spatial extent of the mid-latitude cyclonic anomaly over Far-East Asia is also influenced by the anomalous LH over central–eastern China. While the present findings provide interesting insights into the role of LH anomalies during ISM breaks on the poleward extending meridional wave train, the ACMCC anomaly is found to have important ramifications on the daily rainfall extremes over the Indo-China region. It is revealed from the present analysis that the frequency of extreme rainfall occurrences over Indo-China shows a twofold increase during ISM break periods as compared to active ISM conditions. © 2019, The Author(s).
- ItemMeteorological drivers of extremes in daily stem radius variations of beech, oak, and pine in Northeastern Germany: An event coincidence analysis(Lausanne : Frontiers Media, 2016) Siegmund, Jonatan F.; Sanders, Tanja G.M.; Heinrich, Ingo; van der Maaten, Ernst; Simard, Sonia; Helle, Gerhard; Donner, Reik V.Observed recent and expected future increases in frequency and intensity of climatic extremes in central Europe may pose critical challenges for domestic tree species. Continuous dendrometer recordings provide a valuable source of information on tree stem radius variations, offering the possibility to study a tree's response to environmental influences at a high temporal resolution. In this study, we analyze stem radius variations (SRV) of three domestic tree species (beech, oak, and pine) from 2012 to 2014. We use the novel statistical approach of event coincidence analysis (ECA) to investigate the simultaneous occurrence of extreme daily weather conditions and extreme SRVs, where extremes are defined with respect to the common values at a given phase of the annual growth period. Besides defining extreme events based on individual meteorological variables, we additionally introduce conditional and joint ECA as new multivariate extensions of the original methodology and apply them for testing 105 different combinations of variables regarding their impact on SRV extremes. Our results reveal a strong susceptibility of all three species to the extremes of several meteorological variables. Yet, the inter-species differences regarding their response to the meteorological extremes are comparatively low. The obtained results provide a thorough extension of previous correlation-based studies by emphasizing on the timings of climatic extremes only. We suggest that the employed methodological approach should be further promoted in forest research regarding the investigation of tree responses to changing environmental conditions.
- ItemMultiscale fractal dimension analysis of a reduced order model of coupled ocean–atmosphere dynamics(Göttingen : Copernicus Publ., 2021) Alberti, Tommaso; Donner, Reik V.; Vannitsem, StéphaneAtmosphere and ocean dynamics display many complex features and are characterized by a wide variety of processes and couplings across different timescales. Here we demonstrate the application of multivariate empirical mode decomposition (MEMD) to investigate the multivariate and multiscale properties of a reduced order model of the ocean–atmosphere coupled dynamics. MEMD provides a decomposition of the original multivariate time series into a series of oscillating patterns with time-dependent amplitude and phase by exploiting the local features of the data and without any a priori assumptions on the decomposition basis. Moreover, each oscillating pattern, usually named multivariate intrinsic mode function (MIMF), represents a local source of information that can be used to explore the behavior of fractal features at different scales by defining a sort of multiscale and multivariate generalized fractal dimensions. With these two complementary approaches, we show that the ocean–atmosphere dynamics presents a rich variety of features, with different multifractal properties for the ocean and the atmosphere at different timescales. For weak ocean–atmosphere coupling, the resulting dimensions of the two model components are very different, while for strong coupling for which coupled modes develop, the scaling properties are more similar especially at longer timescales. The latter result reflects the presence of a coherent coupled dynamics. Finally, we also compare our model results with those obtained from reanalysis data demonstrating that the latter exhibit a similar qualitative behavior in terms of multiscale dimensions and the existence of a scale dependency of the statistics of the phase-space density of points for different regions, which is related to the different drivers and processes occurring at different timescales in the coupled atmosphere–ocean system. Our approach can therefore be used to diagnose the strength of coupling in real applications.
- ItemReconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks(München : European Geopyhsical Union, 2017) Franke, Jasper G.; Werner, Johannes P.; Donner, Reik V.Obtaining reliable reconstructions of long-term atmospheric circulation changes in the North Atlantic region presents a persistent challenge to contemporary paleoclimate research, which has been addressed by a multitude of recent studies. In order to contribute a novel methodological aspect to this active field, we apply here evolving functional network analysis, a recently developed tool for studying temporal changes of the spatial co-variability structure of the Earth's climate system, to a set of Late Holocene paleoclimate proxy records covering the last two millennia. The emerging patterns obtained by our analysis are related to long-term changes in the dominant mode of atmospheric circulation in the region, the North Atlantic Oscillation (NAO). By comparing the time-dependent inter-regional linkage structures of the obtained functional paleoclimate network representations to a recent multi-centennial NAO reconstruction, we identify co-variability between southern Greenland, Svalbard, and Fennoscandia as being indicative of a positive NAO phase, while connections from Greenland and Fennoscandia to central Europe are more pronounced during negative NAO phases. By drawing upon this correspondence, we use some key parameters of the evolving network structure to obtain a qualitative reconstruction of the NAO long-term variability over the entire Common Era (last 2000 years) using a linear regression model trained upon the existing shorter reconstruction.
- ItemA Rigorous Statistical Assessment of Recent Trends in Intensity of Heavy Precipitation Over Germany(Lausanne : Frontiers Media, 2019) Passow, Christian; Donner, Reik V.Comprehensive and robust statistical estimates of trends during heavy precipitation events are essential in understanding the impact of past and future climate changes in the hydrological cycle. However, methods commonly used in extreme value statistics (EVS) are often unable to detect significant trends, because of their methodologically motivated reduction of the sample size and strong assumptions regarding the underlying distribution. Here, we propose linear quantile regression (QR) as a complementary and robust alternative to estimating trends in heavy precipitation events. QR does not require any assumptions on the underlying distribution and is also able to estimate trends for the full span of the distribution without any reduction of the available data. As an example, we study here a very dense and homogenized data set of daily precipitation amounts over Germany for the period between 1951 and 2006 to compare the results of QR and the so-called block maxima approach, a classical method in EVS. Both methods indicate an overall increase in the intensity of heavy precipitation events. The strongest trends can be found in regions with an elevation of about 500 m above sea level. In turn, larger spatial clusters of moderate or even decreasing trends can only be found in Northeastern Germany. In conclusion, both methods show comparable results. QR, however, allows for a more flexible and comprehensive study of precipitation events. © Copyright © 2019 Passow and Donner.
- ItemSpatial organization of connectivity in functional climate networks describing event synchrony of heavy precipitation(Berlin ; Heidelberg : Springer, 2021) Wolf, Frederik; Donner, Reik V.In the past years, there has been an increasing number of applications of functional climate networks to studying the spatio-temporal organization of heavy rainfall events or similar types of extreme behavior in some climate variable of interest. Nearly all existing studies have employed the concept of event synchronization (ES) to statistically measure similarity in the timing of events at different grid points. Recently, it has been pointed out that this measure can however lead to biases in the presence of events that are heavily clustered in time. Here, we present an analysis of the effects of event declustering on the resulting functional climate network properties describing spatio-temporal patterns of heavy rainfall events during the South American monsoon season based on ES and a conceptually similar method, event coincidence analysis (ECA). As examples for widely employed local (per-node) network characteristics of different type, we study the degree, local clustering coefficient and average link distance patterns, as well as their mutual interdependency, for three different values of the link density. Our results demonstrate that the link density can markedly affect the resulting spatial patterns. Specifically, we find the qualitative inversion of the degree pattern with rising link density in one of the studied settings. To our best knowledge, such crossover behavior has not been described before in event synchrony based networks. In addition, declustering relieves differences between ES and ECA based network properties in some measures while not in others. This underlines the need for a careful choice of the methodological settings in functional climate network studies of extreme events and associated interpretation of the obtained results, especially when higher-order network properties are considered.
- ItemStatistical mechanics and information-theoretic perspectives on complexity in the Earth system(Basel : MDPI, 2013) Balasis, Georgios; Donner, Reik V.; Potirakis, Stelios M.; Runge, Jakob; Papadimitriou, Constantinos; Daglis, Ioannis A.; Eftaxias, Konstantinos; Kurths, JürgenThis review provides a summary of methods originated in (non-equilibrium) statistical mechanics and information theory, which have recently found successful applications to quantitatively studying complexity in various components of the complex system Earth. Specifically, we discuss two classes of methods: (i) entropies of different kinds (e.g., on the one hand classical Shannon and R´enyi entropies, as well as non-extensive Tsallis entropy based on symbolic dynamics techniques and, on the other hand, approximate entropy, sample entropy and fuzzy entropy); and (ii) measures of statistical interdependence and causality (e.g., mutual information and generalizations thereof, transfer entropy, momentary information transfer). We review a number of applications and case studies utilizing the above-mentioned methodological approaches for studying contemporary problems in some exemplary fields of the Earth sciences, highlighting the potentials of different techniques.
- ItemTropical and mid-latitude teleconnections interacting with the Indian summer monsoon rainfall: a theory-guided causal effect network approach(Göttingen : Copernicus Publ., 2020) Di Capua, Giorgia; Kretschmer, Marlene; Donner, Reik V.; van den Hurk, Bart; Vellore, Ramesh; Krishnan, Raghavan; Coumou, DimThe alternation of active and break phases in Indian summer monsoon (ISM) rainfall at intraseasonal timescales characterizes each ISM season. Both tropical and mid-latitude drivers influence this intraseasonal ISM variability. The circumglobal teleconnection observed in boreal summer drives intraseasonal variability across the mid-latitudes, and a two-way interaction between the ISM and the circumglobal teleconnection pattern has been hypothesized. We use causal discovery algorithms to test the ISM circumglobal teleconnection hypothesis in a causal framework. A robust causal link from the circumglobal teleconnection pattern and the North Atlantic region to ISM rainfall is identified, and we estimate the normalized causal effect (CE) of this link to be about 0.2 (a 1 standard deviation shift in the circumglobal teleconnection causes a 0.2 standard deviation shift in the ISM rainfall 1 week later). The ISM rainfall feeds back on the circumglobal teleconnection pattern, however weakly. Moreover, we identify a negative feedback between strong updraft located over India and the Bay of Bengal and the ISM rainfall acting at a biweekly timescale, with enhanced ISM rainfall following strong updraft by 1 week. This mechanism is possibly related to the boreal summer intraseasonal oscillation. The updraft has the strongest CE of 0.5, while the Madden–Julian oscillation variability has a CE of 0.2–0.3. Our results show that most of the ISM variability on weekly timescales comes from these tropical drivers, though the mid-latitude teleconnection also exerts a substantial influence. Identifying these local and remote drivers paves the way for improved subseasonal forecasts.